Statistical Methods for Six Sigma
IN R&D and Manufacturing
(Sprache: Englisch)
The ideas of process control and reducing variability are hot topics in industry today, the food industry included. Statistical process control (SPC)--or statistical quality control--is a key aspect of any quality assurance program. This book helps readers...
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The ideas of process control and reducing variability are hot topics in industry today, the food industry included. Statistical process control (SPC)--or statistical quality control--is a key aspect of any quality assurance program. This book helps readers understand the effects of variation on processes and the statistical concepts and measures underpinning SPC critical to reducing variation, improving quality and performance, and making sound decisions in industry.
Klappentext zu „Statistical Methods for Six Sigma “
A guide to achieving business successes through statistical methodsStatistical methods are a key ingredient in providing data-based guidance to research and development as well as to manufacturing. Understanding the concepts and specific steps involved in each statistical method is critical for achieving consistent and on-target performance.
Written by a recognized educator in the field, Statistical Methods for Six Sigma: In R&D and Manufacturing is specifically geared to engineers, scientists, technical managers, and other technical professionals in industry. Emphasizing practical learning, applications, and performance improvement, Dr. Joglekar's text shows today's industry professionals how to:
* Summarize and interpret data to make decisions
* Determine the amount of data to collect
* Compare product and process designs
* Build equations relating inputs and outputs
* Establish specifications and validate processes
* Reduce risk and cost-of-process control
* Quantify and reduce economic loss due to variability
* Estimate process capability and plan process improvements
* Identify key causes and their contributions to variability
* Analyze and improve measurement systems
This long-awaited guide for students and professionals in research, development, quality, and manufacturing does not presume any prior knowledge of statistics. It covers a large number of useful statistical methods compactly, in a language and depth necessary to make successful applications. Statistical methods in this book include: variance components analysis, variance transmission analysis, risk-based control charts, capability and performance indices, quality planning, regression analysis, comparative experiments, descriptive statistics, sample size determination, confidence intervals, tolerance intervals, and measurement systems analysis. The book also contains a wealth of case studies and examples, and features a unique test to evaluate the reader's
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understanding of the subject.
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Inhaltsverzeichnis zu „Statistical Methods for Six Sigma “
1. Introduction2. Basic Statistics
2.1 Descriptive Statistics
2.2 Statistical Distributions
2.3 Confidence Intervals
2.4 Sample Size
2.5 Tolerance Intervals
2.6 Normality, Independence and Homoscedasticity
3. Comparative Experiments and Regression Analysis
3.1 Hypothesis Testing Framework
3.2 Comparing Single Population
3.3 Comparing Two Populations
3.4 Comparing Multiple Populations
3.5 Correlation
3.6 Regression Analysis
4. Control Charts
4.1 Role of Control Charts
4.2 Logic of Control Limits
4.3 Variable Control Charts
4.4 Attribute Control Charts
4.5 Interpreting Control Charts
4.6 Key Success Factors
5. Process Capability
5.1 Capability and Performance Indices
5.2 E stimating Capability and Performance Indices
5.3 Six-Sigma Goal
5.4 Planning for Improvement
6. Other Useful Charts
6.1 Risk-based Control Ch arts
6.2 Modified Control Limit Chart
6.3 Moving Average Control Chart
6.4 Short Run Control Charts
6.5 Charts for Non-Normal Distributions
7. Variance Components Analysis
7.1 Chart (Random Factor)
7.2 One-way Classification (Fixed Factor)
7.3 Structured Studies and Variance Components
8. Quality Planning with Variance Components
8.1 Typical Manufacturing Application
8.2 Economic Loss Functions
8.3 Planning for Quality Improvement
8.4 Application to Multi-Lane Manufacturing Process
8.5 Variance Transmission Analysis
8.6 Application to a Factorial Design
8.7 Variance Components and Specifications
9. Measurement Systems Analysis
9.1 Statistical Properties of Measurement Systems
9.2 Acceptance Criteria
9.3 Calibration Study
9.4 Stability and Bias Study
9.5 Repeatability and Reproducibility (R&R) Study
9.6 Robustness and Intermediate Precision Studies
9.7 Linearity Study
9.8 Method Transfer Study
9.9 Calculating Significant Figures
10. What Color is Your Belt?
10.1 Test
10.2 Answers
Appendix
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A: Tail Area of Unit Normal Distribution
Appendix B: Probability Points of the t Distribution with v Degrees of Freedom
Appendix C: Probability Points of the x^2 Distribution with v Degrees of Freedom
Appendix D1.k Values for Two-Sided Normal Tolerance Limits
Appendix D2.k Values for One-Sided Normal Tolerance Limits
Appendix E1: Percentage Points of the F Distribution: Upper 5% Points
Appendix E2: Percentage Points of the F Distribution: Upper 2.5% Points
Appendix F: Critical Values of Hartley's Maximum F Ratio Test for Homogeneity of Variances
Appendix G: Table of Control Chart Constants
Glossary Of Symbols
References
Index
Appendix B: Probability Points of the t Distribution with v Degrees of Freedom
Appendix C: Probability Points of the x^2 Distribution with v Degrees of Freedom
Appendix D1.k Values for Two-Sided Normal Tolerance Limits
Appendix D2.k Values for One-Sided Normal Tolerance Limits
Appendix E1: Percentage Points of the F Distribution: Upper 5% Points
Appendix E2: Percentage Points of the F Distribution: Upper 2.5% Points
Appendix F: Critical Values of Hartley's Maximum F Ratio Test for Homogeneity of Variances
Appendix G: Table of Control Chart Constants
Glossary Of Symbols
References
Index
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Autoren-Porträt von Anand M. Joglekar
ANAND M. JOGLEKAR, PhD, is the President of Joglekar Associates, Inc., which provides education, consulting, and software to help companies achieve business successes through the application of statistical methods. He received his PhD in engineering with extensive statistics education from the University of Wisconsin, Madison. As a practicing engineer-statistician he has implemented statistical methods in various functions within a company to accelerate development, achieve high quality, and reduce cost. He has taught statistical methods to thousands of industry participants through in-house seminars or seminars sponsored by industry associations such as the Institute of Food Technologists. His clients include major companies in automotive, biotechnology, computer, defense, food, medical device, mining, packaging, pharmaceutical, semiconductor, and many other industries.
Bibliographische Angaben
- Autor: Anand M. Joglekar
- 2003, 1. Auflage, 300 Seiten, Maße: 25,8 cm, Gebunden, Englisch
- Verlag: Wiley & Sons
- ISBN-10: 0471203424
- ISBN-13: 9780471203421
Sprache:
Englisch
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